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Aim: To compare the effectiveness of different basal insulins (BI) prescribed as an add‐on to or switch from glucagon‐like peptide‐1 receptor agonist (GLP‐1 RA) therapy. Materials and Methods: Retrospective, real‐world data from electronic medical records of 32 Italian diabetes clinics were used, after propensity score adjustment, to compare effectiveness after 6 months of treatment with second‐ versus first‐generation BI (2BI vs. 1BI) or glargine 300 U/ml versus degludec 100 U/ml (Gla‐300 vs. Deg‐100), when added to (ADD‐ON) or in substitution of (SWITCH) GLP‐1 RA. Only comparisons, including a minimum of 100 patients per group, were performed to ensure adequate robustness of the analyses. Results: In the ADD‐ON cohort (N = 700), greater benefits of 2BI versus 1BI were found in glycated haemoglobin {HbA1c; estimated mean difference: −0.32% [95% confidence interval (CI) −0.62; −0.02]; p =.04} and fasting blood glucose [FBG; −20.73 mg/dl (95% CI −35.62; −5.84); p =.007]. In the SWITCH cohort (N = 2097), greater benefits of 2BI versus 1BI were found in HbA1c [−0.22% (95% CI −0.42; −0.02); p =.03], FBG [−10.15 mg/dl (95% CI −19.04; −1.26); p =.03], and body weight [−0.67 kg (95% CI −1.30; −0.04); p =.04]. In the SWITCH cohort starting 2BI (N = 688), marked differences in favour of Gla‐300 versus Deg‐100 were documented in HbA1c [−0.89% (95% CI −1.26; −0.52); p <.001] and FBG [−17.89 mg/dl (95% CI −32.45; −3.33); p =.02]. Using propensity score matching as a sensitivity analysis, the benefit on HbA1c was confirmed [−0.55% (95% CI –1.02; −0.08); p =.02]. BI titration was suboptimal in all examined cohorts. Conclusions: 2BI are a valuable option to intensify GLP‐1 RA therapy. Switching to Gla‐300 versus Deg‐100 was associated with greater HbA1c improvement. [ABSTRACT FROM AUTHOR]

Add-on of basal insulin (BI) to intensify the ongoing therapy with glucagon-like peptide 1 receptor agonist (GLP-1 RA) is recommended, but it is unclear if free or fixed combination of BI and GLP-1 RA produce similar outcomes. A retrospective comparative effectiveness analysis of the add-on of glargine 300 U/mL (Gla-300) to ongoing GLP-1 RA vs. switch to fixed ratio combination of degludec and liraglutide (iDegLira) was performed. Real-world data collected in electronic medical records by 32 Italian diabetes clinics. Propensity score (PS) adjustment was applied to assess changes in glycated hemoglobin (HbA1c), fasting blood glucose (FBG), body weight, and BI dose after 6 months from Gla-300 or iDegLira initiation. Compared to iDegLira group (N = 260), Gla-300+GLP-1 RA group (N = 255) had older age and higher levels of HbA1c (9.1 vs. 8.9%). After 6 months, statistically significant greater FBG improvement [estimated mean difference and 95% confidence intervals: −24.05 mg/dl (−37.04; −11.06; p = 0.0003) and BI dose increase [+0.03 U/kg (95%CI 0.00; 0.06); p = 0.009] were found in the free vs. fixed combination group, although low doses of BI (0.2 U/kg) were reached in both groups. Trends of larger HbA1c and body weight reductions with the free combination were also found, without reaching the statistical significance. Although inertia in insulin initiation and titration was documented in both groups, higher benefit on FBG control was obtained with free vs. fixed combination, likely due to a better titration of BI and GLP-1 RA. • Addition of basal insulin (BI) to GLP-1 RA is a recommended intensification approach. • It is unclear if starting BI in free or fixed combination with GLP-1 RA produce similar results. • Larger benefit on fasting blood glucose was obtained with free vs. fixed combination. • A better titration of BI and GLP-1 RA was documented with the free combination. • Clinical inertia in titration was documented in both approaches. [ABSTRACT FROM AUTHOR]

Aims: Glomerular hyperfiltration characterises the earliest stage of diabetic nephropathy and predicts adverse kidney and cardiovascular outcomes. We aimed to assess the prevalence and risk factors of glomerular hyperfiltration in a population‐based contemporary cohort of individuals with type 2 diabetes (T2D). Materials and Methods: The prevalence of unequivocal glomerular hyperfiltration (defined by an estimated glomerular filtration rate >120 mL/min/1.73 m2) and its associated risk factors were identified in a cohort of 202,068 adult patients with T2D receiving specialist care in 2021–2022, whose center‐aggregated data were automatically extracted from electronic medical records of 75 diabetes clinics in Italy. Results: Glomerular hyperfiltration was identified in 1262 (0.6%) participants. The prevalence of glomerular hyperfiltration varied widely across centers (0%–3.4%) and correlated with mean center age, HbA1c, body mass index (BMI), and low‐density lipoprotein cholesterol. Patients in centers with high glomerular hyperfiltration prevalence (>0.8%) were more often men and had lower age and BMI, but more frequent albuminuria and worse glucose, lipid, and blood pressure control, compared with low‐normal prevalence centers. Conclusions: Unequivocal glomerular hyperfiltration can be identified in up to 3.4% of patients receiving up‐to‐date specialist diabetes care. Glomerular hyperfiltration prevalence varies across centers and substantially increases with suboptimal control of metabolic risk factors, which would require improved management to mitigate the negative health consequences of this pathological condition. [ABSTRACT FROM AUTHOR]

Background: International guidelines for diabetes care emphasize the urgency of promptly achieving and sustaining adequate glycemic control to reduce the occurrence of micro/macrovascular complications in patients with type 2 diabetes mellitus (T2DM). However, data from the Italian Association of Medical Diabetologists (AMD) Annals reveal that only 47% of T2DM patients reach appropriate glycemic targets, with approximately 30% relying on insulin therapy, either solely or in combination. This artificial intelligence analysis seeks to assess the potential impact of timely insulin initiation in all eligible patients via a "what-if" scenario simulation, leveraging real-world data. Methods: This retrospective cohort study utilized the AMD Annals database, comprising 1,186,247 T2DM patients from 2005 to 2019. Employing the Logic Learning Machine (LLM), we simulated timely insulin use for all eligible patients, estimating its effect on glycemic control after 12 months within a cohort of 85,239 patients. Of these, 20,015 were employed for the machine learning phase and 65,224 for simulation. Results: Within the simulated scenario, the introduction of appropriate insulin therapy led to a noteworthy projected 17% increase in patients meeting the metabolic target after 12 months from therapy initiation within the cohort of 65,224 individuals. The LLM's projection envisages 32,851 potential patients achieving the target (hemoglobin glycated < 7.5%) after 12 months, compared to 21,453 patients observed in real-world cases. The receiver operating characteristic (ROC) curve analysis for this model demonstrated modest performance, with an area under the curve (AUC) value of 70.4%. Conclusions: This study reaffirms the significance of combatting therapeutic inertia in managing T2DM patients. Early insulinization, when clinically appropriate, markedly enhances patients' metabolic goals at the 12-month follow-up. [ABSTRACT FROM AUTHOR]

To assess intensification approaches with basal insulin (BI) following glucagon-like peptide-1 receptor agonist (GLP-1 RA) treatment in type 2 diabetes (T2D). Real-world data were collected in electronic medical records by 32 Italian diabetes clinics between 2011 and 2021. Primary endpoint was the proportion of insulin-naïve T2D patients treated with GLP-1 RA who initiated (add-on or switch) BI. Secondary endpoints were: treatment approaches, mean time to BI start, effectiveness and safety. Among 7,962 eligible patients, BI was prescribed to 3,164 (39.7%; 95%CI 38.7; 40.8): 67.6% switched to BI (22.1% also starting 1–3 injections of short-acting insulin), 22.7% added BI while maintaining GLP-1 RA, and 9.7% switched to a fixed-ratio combination of GLP-1 RA and BI (FRC). Median time since the first GLP-1 RA to BI/FRC prescription was 27.4 (IQ range 11.8–53.5) months. In this study 60.3% of patients did not start BI/FRC, among whom 15.2% intensified GLP-1 RA therapy with other oral agents. Effectiveness and safety were documented in all intensification approaches with BI/FRC, but HbA1c level at intensification time of ≥9.0% and suboptimal BI titration suggested clinical inertia. Use of second generation BI and add-on to GLP-1 RA schemes increased over time and effectiveness improved. Clinical inertia should be overcome using innovative insulin options. Timely combination therapy of BI and GLP-1 RA is a valuable choice. • Real world data on therapeutic approaches after GLP-1 RA treatment are missing. • Basal insulin plays a key role in intensifying previous therapy with GLP-1 RA. • RESTORE-G study found that about 40% of the patients intensified GLP1-RA with basal insulin. • Add-on (free or fixed combination) or switch schemes are adopted. • Effectiveness and safety of intensification approaches, but also clinical inertia, were documented. [ABSTRACT FROM AUTHOR]

(1) Background: Oral semaglutide represents the first oral GLP-1 RA approved for the treatment of type 2 diabetes mellitus (T2DM). This real-world retrospective study aimed at evaluating its effectiveness and tolerability in the treatment of patients with T2DM when patients switched from a glucose-lowering agent to it and when it was added to the usual therapy. (2) Methods: Adult patients with T2DM taking oral semaglutide and followed in the ASUGI Diabetes Center were identified with the use of electronic medical records between October 2022 and May 2023. (3) Results: A total of 129 patients were recruited. The median follow-up was 6 months. Be it as a switchover or as an add-on therapy, oral semaglutide significantly reduced HbA1c and BMI. Switching from DPPIV inhibitors to oral semaglutide was associated with a significant reduction in HbA1c and BMI, switching from SGLT2 inhibitors was associated with a significant reduction in HbA1c, and switching from sulphonylureas was associated with a significant reduction in BMI. The median HbA1c change was associated with baseline HbA1c. SBP significantly decreased in the add-on group. Oral semaglutide was well tolerated. (4) Conclusions: This study shows that in the real-world setting, oral semaglutide is effective and safe as a switchover or as an add-on therapy for the treatment of T2DM. [ABSTRACT FROM AUTHOR]

Identifying and treating lipid abnormalities is crucial for preventing cardiovascular disease in diabetic patients, yet only two-thirds of patients reach recommended cholesterol levels. Elucidating the factors associated with lipid goal attainment represents an unmet clinical need. To address this knowledge gap, we conducted a real-world analysis of the lipid profiles of 11.252 patients from the Annals of the Italian Association of Medical Diabetologists (AMD) database from 2005 to 2019. We used a Logic Learning Machine (LLM) to extract and classify the most relevant variables predicting the achievement of a low-density lipoprotein cholesterol (LDL-C) value lower than 100 mg/dL (2.60 mmol/L) within two years of the start of lipid-lowering therapy. Our analysis showed that 61.4% of the patients achieved the treatment goal. The LLM model demonstrated good predictive performance, with a precision of 0.78, accuracy of 0.69, recall of 0.70, F1 Score of 0.74, and ROC-AUC of 0.79. The most significant predictors of achieving the treatment goal were LDL-C values at the start of lipid-lowering therapy and their reduction after six months. Other predictors of a greater likelihood of reaching the target included high-density lipoprotein cholesterol, albuminuria, and body mass index at baseline, as well as younger age, male sex, more follow-up visits, no therapy discontinuation, higher Q-score, lower blood glucose and HbA1c levels, and the use of anti-hypertensive medication. At baseline, for each LDL-C range analysed, the LLM model also provided the minimum reduction that needs to be achieved by the next six-month visit to increase the likelihood of reaching the therapeutic goal within two years. These findings could serve as a useful tool to inform therapeutic decisions and to encourage further in-depth analysis and testing. [ABSTRACT FROM AUTHOR]

Night shift work has been found to be associated with a higher risk of cardiovascular and cerebrovascular disease. One of the underlying mechanisms seems to be that shift work promotes hypertension, but results have been variable. This cross-sectional study was carried out in a group of internists with the aim of performing a paired analysis of 24 h blood pressure in the same physicians working a day shift and then a night shift, and a paired analysis of clock gene expression after a night of rest and a night of work. Each participant wore an ambulatory blood pressure monitor (ABPM) twice. The first time was for a 24 h period that included a 12 h day shift (08.00–20.00) and a night of rest. The second time was for a 30 h period that included a day of rest, a night shift (20.00–08.00), and a subsequent period of rest (08.00–14.00). Subjects underwent fasting blood sampling twice: after the night of rest and after the night shift. Night shift work significantly increased night systolic blood pressure (SBP), night diastolic blood pressure (DBP), and heart rate (HR) and decreased their respective nocturnal decline. Clock gene expression increased after the night shift. There was a direct association between night blood pressure and clock gene expression. Night shifts lead to an increase in blood pressure, non-dipping status, and circadian rhythm misalignment. Blood pressure is associated with clock genes and circadian rhythm misalignement. [ABSTRACT FROM AUTHOR]

Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. The present study is aimed to build an artificial intelligence (AI) prognostic model that takes in account a large and heterogeneous set of clinical factors and investigates the risk of developing HF in diabetic patients. We carried out an electronic health records- (EHR-) based retrospective cohort study that included patients with cardiological clinical evaluation and no previous diagnosis of HF. Information consists of features extracted from clinical and administrative data obtained as part of routine medical care. The primary endpoint was diagnosis of HF (during out-of-hospital clinical examination or hospitalization). We developed two prognostic models using (1) elastic net regularization for Cox proportional hazard model (COX) and (2) a deep neural network survival method (PHNN), in which a neural network was used to represent a non-linear hazard function and explainability strategies are applied to estimate the influence of predictors on the risk function. Over a median follow-up of 65 months, 17.3% of the 10,614 patients developed HF. The PHNN model outperformed COX both in terms of discrimination (c-index 0.768 vs 0.734) and calibration (2-year integrated calibration index 0.008 vs 0.018). The AI approach led to the identification of 20 predictors of different domains (age, body mass index, echocardiographic and electrocardiographic features, laboratory measurements, comorbidities, therapies) whose relationship with the predicted risk correspond to known trends in the clinical practice. Our results suggest that prognostic models for HF in diabetic patients may improve using EHRs in combination with AI techniques for survival analysis, which provide high flexibility and better performance with respect to standard approaches. [ABSTRACT FROM AUTHOR]

Aims: To investigate the effects of glucose‐lowering agents on all‐cause mortality, and cardiovascular and renal outcomes in adults with type 2 diabetes. Methods: A MEDLINE and EMBASE search was performed to identify randomized controlled trials, published up to 28 February 2022, with a follow‐up ≥52 weeks, in which glucose‐lowering drugs were compared with either placebo or active comparators. We included only trials reporting formal external adjudication of events. All‐cause mortality, 3‐point MACE (major cardiovascular events), and hospitalization for heart failure (HHF) were considered as principal outcomes. Doubling of serum creatinine, worsening albuminuria, and renal death were considered as secondary endpoints. Results: We included randomized controlled trials performed on metformin (n = 17), pioglitazone (n = 20), alpha‐glucosidase inhibitors (n = 9), insulin secretagogues (n = 42), dipeptidyl‐peptidase‐4 inhibitors (n = 67), glucagon‐like peptide‐1 receptor agonists (n = 45) or sodium‐glucose co‐transporter‐2 inhibitors (SGLT‐2i; n = 42) and insulin (n = 18). Glucagon‐like peptide‐1 receptor agonist and SGLT‐2i were associated with a significant reduction in all‐cause mortality [Mantel‐Haenszel odds ratio (MH‐OR), 95% confidence interval: 0.88 (0.83; 0.95) and 0.85 (0.79; 0.91), respectively] and MACE [MH‐OR, 95% confidence interval: 0.89 (0.84; 0.94) and 0.90 (0.84; 0.96), respectively]. SGLT‐2i was associated with a reduced risk of HHF [MH‐OR 0.68 (0.62; 0.75)], worsening albuminuria [MH‐OR 0.67 (0.55; 0.80)] and doubling of serum creatinine [MH‐OR 0.58 (0.44; 0.79)]. Metformin and pioglitazone were associated with a significantly lower risk of MACE [MH‐OR 0.60 (0.47; 0.80) and 0.85 (0.74; 0.97), respectively] and pioglitazone with a higher risk of HHF [MH‐OR 1.30 (1.04; 1.62)]. Insulin secretagogues were associated with increased risk of all‐cause mortality [MH‐OR 1.12 (1.01; 1.24)] and MACE [MH‐OR 1.19 (1.02; 1.39)]. Conclusions: The results of this updated meta‐analysis need to be considered in the choice of drug treatment for type 2 diabetes mellitus, which cannot be merely based on the effect of glucose‐lowering drugs on long‐term glycaemic control. [ABSTRACT FROM AUTHOR]

Background and Aims: The renin-angiotensin system (RAS), which is a key mediator of cardiovascular homeostasis, has two main axes. The classic one, including angiotensin-converting enzyme (ACE) and Angiotensin (Ang) II, promoting vasoconstriction, and the "alternative" one, including ACE2 and Ang1-7, with opposed actions to AngII. ACE2 has been identified as the main receptor of SARS-CoV2, whereby it enters the cells, leading to the downregulation of surface ACE2 and RAS tissue unbalance. Given that diabetes is associated with an increase in COVID-19 severity and death, we aimed at evaluating RAS expression in patients with type 1 diabetes (T1D).Methods and Results: This is a case-control study comparing 39 T1D patients to 33 controls, with a median age of 29 and 32 years, and no comorbidities. ACE and ACE2 gene expression was assessed in peripheral blood mononuclear cells. T1D patients had higher ACE expression and circulating AngII, which were related to glucose levels. T1D patients had lower ACE2 expression. However, ACE2 expression was also related to the sex of participants, being higher in the female group. T1D women did not show the same increase of ACE2 expression that was seen in control women.Conclusion: T1D promotes the increase of ACE, AngII, and ACE/ACE2, which might contribute to the higher cardiovascular risk, as well as to severe tissue injury induced by SARS-CoV2 in these patients. The ratio ACE/ACE2 does not differ between men and women with T1D, which might explain why CVD or COVID-19 do not show substantial gender differences in these patients. [ABSTRACT FROM AUTHOR]

Aim: In 2019, the Italian Society of Diabetology and the Italian Association of Clinical Diabetologists nominated an expert panel to develop guidelines for drug treatment of type 2 diabetes. After identifying the effects of glucose-lowering agents on major adverse cardiovascular events (MACEs), all-cause mortality, and hospitalization for heart failure (HHF) as critical outcomes, the experts decided to perform a systematic review and meta-analysis on the effect of pioglitazone with this respect.Data Synthesis: A MEDLINE database search was performed to identify RCTs, up to June 1st, 2021, with duration≥52 weeks, in which pioglitazone was compared with either placebo or active comparators. The principal endpoints were MACE and HHF (restricted for RCT reporting MACEs within their outcomes), all-cause mortality (irrespective of the inclusion of MACEs among the pre-specified outcomes). Mantel-Haenszel odds ratio (MH-OR) with 95% Confidence Interval (95% CI) was calculated for all the endpoints considered. Eight RCTs were included in the analysis for MACEs and HF (5048 and 5117 patients in the pioglitazone and control group, respectively), and 24 in that for all-cause mortality (10,682 and 9674 patients). Pioglitazone neither significantly increased nor reduced the risk of MACE, all-cause mortality, and HHF in comparison with placebo/active comparators (MH-OR: 0.90, 95% CI 0.78-1.03, 0.91, 95% CI 0.77, 1.09, and 1.16, 95% CI 0.73, 1.83, respectively). Pioglitazone was associated with a significant reduction of MACE in patients with prior cardiovascular events (MH-OR 0.84, 95% CI 0.72-0.99).Conclusions: This meta-analysis showed no significant effects of pioglitazone on incident MACE, all-cause mortality, and HHF. [ABSTRACT FROM AUTHOR]

Aim: Alpha-glucosidase inhibitors are approved drugs for treating type 2 diabetes (T2DM); however, their effects on mortality and cardiovascular safety are unclear. This meta-analysis was aimed at evaluating the effects of alpha-glucosidase inhibitors on all-cause mortality and major cardiovascular events (MACE).Data Synthesis: A Medline, Embase, Cochrane database searching for alpha-glucosidase inhibitors was performed up to July 1st, 2021. All randomized controlled trials (RCT) with a duration ≥52 weeks and comparing the effects of alpha-glucosidase inhibitors with placebo or active drugs were collected. Further inclusion criteria were: RCT reporting MACE within their primary outcome, or as pre-defined secondary outcome; and RCT enrolling at least 100 patients with T2DM. Mantel-Haenszel odds ratio (MH-OR) with 95% confidence intervals were calculated for the aforementioned outcomes. A total of eight RCTs, enrolling 1124 and 908 patients on alpha-glucosidase inhibitors and comparators, respectively, were identified. No trials reported information on MACE. Treatment with alpha-glucosidase inhibitors was not associated with a significant increase of all-cause mortality compared with other therapies or no therapy/placebo (MH-OR 0.76 [0.28; 2.05]).Conclusions: The evidence of beneficial or detrimental effects of alpha-glucosidase inhibitors on all-cause mortality and cardiovascular events is not sufficient to draw any conclusions. [ABSTRACT FROM AUTHOR]

This document illustrates the results of the work of two interdisciplinary and multistakeholder panels (researchers, public institutions, and industry representatives) on drug territorialization and digitalization, organized as part of a residential seminar held on 30 September and 1st October 2021. Arising from some considerations about the demand for health and the provisions of the National Recovery and Resilience Plan (PNRR), the discussion touched various aspects of managing the transition from current to future management models. The importance of identifying criteria for prioritizing interventions in the area emerged: different methods of drug delivery, scientific information and measurement, re-evaluation of pathologies that can be managed in this area. Finally, the role of digitization within this change was explored. The opinions provided by the experts move towards making the most of the opportunities arising from PNRR, in terms of investments in healthcare and data application, with a view to improve health system efficiency, patient care and related outcomes. [ABSTRACT FROM AUTHOR]